An Assessment of High-Density UAV Point Clouds for the Measurement of Young Forestry Trials

Abstract

The measurement of forestry trials is a costly and time-consuming process. Over the past few years, unmanned aerial vehicles (UAVs) have provided some significant developments that could improve cost and time efficiencies. However, little research has examined the accuracies of these technologies for measuring young trees. This study compared the data captured by a UAV laser scanning system (ULS), and UAV structure from motion photogrammetry (SfM), with traditional field-measured heights in a series of forestry trials in the central North Island of New Zealand. Data were captured from UAVs, and then processed into point clouds, from which heights were derived and compared to field measurements. The results show that predictions from both ULS and SfM were very strongly correlated to tree heights (R2 = 0.99, RMSE = 5.91%, and R2 = 0.94, RMSE = 18.5%, respectively) but that the height underprediction was markedly lower for ULS than SfM (Mean Bias Error = 0.05 vs. 0.38 m). Integration of a ULS DTM to the SfM made a minor improvement in precision (R2 = 0.95, RMSE = 16.5%). Through plotting error against tree height, we identified a minimum threshold of 1 m, under which the accuracy of height measurements using ULS and SfM significantly declines. Our results show that SfM and ULS data collected from UAV remote sensing can be used to accurately measure height in young forestry trials. It is hoped that this study will give foresters and tree breeders the confidence to start to operationalise this technology for monitoring trials.

Comparing 3D Point Cloud Data from Laser Scanning and Digital Aerial Photogrammetry for Height Estimation of Small Trees and Other Vegetation in a Boreal–Alpine Ecotone

“…This result is nevertheless consistent with recent findings reported by Ref. [26]. Whether this is a general phenomenon or other DAP algorithms/software packages and parameter settings would produce substantially different results is unknown and out of the scope of the current study.…”

“…In an assessment of UAS 3D point clouds from laser and DAP for individual tree height estimation over tree plantations with an average tree height of 2.6 m, Ref. [26] reported that DAP underestimated height to a greater extent than laser and that the accuracy was greater for laser than for DAP. However, their 3D data had an exceptionally high point density (443-939 points m −2 for DAP and 325-649 points m −2 for laser), which makes comparisons with previous findings based on data from airborne platforms and coarser resolution imagery difficult.…”

“…There are currently no commercial interests associated with small trees and other vegetation in the tree line ecotones, as there are in the productive forests where small trees represent young forest in an early stage of a rotation after clear-felling (cf. [25,26]). The primary purposes of quantifying and monitoring small trees and other vegetation in the tree line ecotones is therefore partly to keep track of how climate change affects this climate sensitive ecological environment and to enable consistent analysis of the net climate feedback of tree line migration caused by changes in biomass and soil carbon pools and changes in albedo.…”

Parameter Measurement of Live Animals Based on the Mirror of Multiview Point Cloud

“…., n}, respectively. Under the premise of minimizing the error function error(G, p) between the two point sets in formula (8), the least squares method can be adopted to iteratively perform the optimal coordinate transform and calculate the rotation matrix and translation matrix until the preset error threshold or maximum number of iterations is reached:…”

“…Large-scale, standardized breeding can effectively improve the output and profit of pigs, cattle, and sheep. During large-scale, standardized breeding, the selective breeding of good livestock breeds hinges on the accurate measurement of body parameters for live animals [5][6][7][8][9][10][11][12].…”